Project Summary Insufficient sleep (IS), stemming from sleep apnea, shift work, insomnia, working over 40 hr./week, unfavorable sleep environments and/or volitional reduction of bedtime, is associated with increased risk of cardiovascular disease (CVD) markers (elevated blood pressure, insulin resistance, dyslipidemia and arterial stiffness), inflammatory markers (interleukin-6, tumor necrosis factor-?, and C-reactive protein) as well as with brain injury. Compelling evidence shows racial/ethnic disparities in insufficient sleep (IS), with blacks exhibiting a three-fold greater risk of IS relative to whites. Disparities might arise from physiologic and genetic factors, but recent evidence suggests environmental and psychosocial factors are also critical determinants. This study will utilize innovative dynamic modeling in a multi-level framework to delineate the psychosocial and environmental determinants (associative factors) of actigraphic IS and its putative associations with adverse health outcomes among blacks. Individual- and contextual-level data will be captured using novel home-based recordings and GIS data to model the environmental context where sleep occurs. The proposed study will leverage success of the NYU Sleep Disparity Workgroup led by Dr. Jean- Louis (PI), who has been conducting community-engaged sleep research for over 10 years. The workgroup comprises outstanding investigators with expertise in sleep and circadian rhythm, CVD, brain health, health disparities, translational behavioral medicine, and multi-level dynamic modeling. The study will benefit from experience of our standing Community Steering Committee, enabling recruitment of 560 blacks in various venues to participate in weeklong home studies to achieve proposed study aims. The multidisciplinary team will: 1) identify psychosocial (social support, discrimination, and attitudes/beliefs) and environmental (household [density, noise, light, and temperature], socioeconomic position, social capital, and neighborhood [built environment]) factors that are associated with IS; ascertain effects of IS on (a) markers of CVD (obesity, BP, lipid profile, and glucose/ HbA1C) and inflammation (IL-6, IL-10, and TNF-?) and on (b) markers of brain injury (tau, amyloid-?, neurofilament light, homocysteine, and glial fibrillary acidic protein; and develop profiles of blacks with IS-related adverse health outcomes using individual- and environmental-level data applying innovative multi-level dynamic modeling tools (Bayesia Belief Network and Agent-Based Simulation). This study will provide evidence to delineate factors underlying greater rates of IS among blacks and explain putative associations with markers of CVD, inflammation, and brain injury. These data will provide the foundation for longitudinal studies assessing causal effects of IS on these novel markers and interventions to mitigate adverse effects of IS on health outcomes.